LehreAbschlussarbeiten
Master- und Projektarbeiten bei Prof. Calà Lesina in der AG "Computational Photonics" offen

Master- und Projektarbeiten bei Prof. Calà Lesina in der AG "Computational Photonics" offen

© Oleg Magni/Pexels.com/bearb. PhoenixD

Im Bereich Optik und Photonik sind in der Forschungsgruppe "Computational Physics" bei Prof. Calà Lesina verschiedene Themen für Masterarbeiten zu vergeben. Je nach Qualifikation des Kandidaten/der Kandidatin kann es sich auch um eine Studienarbeit handeln. Prof. Calà Lesina ist Mitglied von PhoenixD und Teamleiter der Forschungsgruppe "Computational Photonics" am HOT - Hannover Centre for Optical Technologies.

Folgende Arbeiten sind zu vergeben:

1) Import of complex CAD geometries into in-house nanophotonics software

My group develops in-house a 3D Maxwell’s equations solver by exploiting parallel computing and the finite-difference time-domain (FDTD) method. The software is used to study how light interacts with nanostructured materials, so called metamaterials, to obtain optical properties beyond what the material itself can achieve. We currently cannot simulate geometries created with a CAD software, such as Solidworks or AutoCAD. The student will work on this integration. This will enable the simulation of highly complex geometries in nanophotonics.

2) Inverse design of nanophotonic structures with deep neural networks

Optical metasurfaces represent a revolutionary tool to manipulate the behaviour of light at the nanoscale. They can reduce the footprint of traditional optical components, e.g., flat lenses, and achieve optical properties otherwise not available (tunable beam steering, wavefront manipulation, etc), thus finding applications in all domains of optics and photonics. The design of metasurfaces rely on full-wave simulations combined with optimization algorithms, such as topology optimization, genetic algorithms, and particle swarm. In recent years, deep neural networks have been introduced for the inverse design of metasurfaces and nanostructured materials in general. The student will develop deep neural network techniques for the inverse design of optical metasurfaces.

Erforderliche Qualifikationen für alle Projekte/Abschlussarbeiten:

  • Sehr gute Programmierkenntnisse,
  • Sehr gute Kenntnisse der Theorie elektromagnetischer Felder,
  • Sehr gute Kommunikation in Englisch.

To apply please send CV and transcripts to the office of Prof. Antonio Calà Lesina (office-calalesina@hot.uni-hannover.de).